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agentx.sale Text Classifier
x402
agentx.sale Text Classifier is a paid API for AI agents from agentx.sale, paid per call via x402, $1.75/call, status unknown (last checked 2026-10-21).
Classifies supplied text into free-form or caller-defined topic labels with confidence scores and rationale, supporting single-label and multi-label modes
Price / call$1.75
Success—
StatusUnknown
How this service works
AI topic classification of supplied text: free-form topics or caller-supplied label set, single or multi-label, confidence + rationale. POST JSON {text, labels?, multiLabel?} (max 24k chars)
Output
Returns the assigned topic label(s), a confidence score (0–1) for each, and a brief rationale explaining why the text was assigned to those categories. In multi-label mode, multiple labels with individual scores are returned.
Example use cases
Support ticket routing by topic
“Classify this incoming support message into one of these labels — billing, account, shipping, returns, or technical — and tell me the confidence score: 'I was charged twice for the same order and my login stopped working after.'”
Multi-label tagging of a news article
“Tag this news article with all relevant topics it covers — use multi-label mode and pick from: politics, economy, health, environment, technology, sports: 'The senate passed new climate legislation tied to a renewable energy investment package.'”
Zero-shot free-form topic detection
“What is this paragraph mainly about? Just figure out the topics yourself without me providing labels — and give me your confidence and reasoning: 'Ketamine-assisted therapy showed a 60% remission rate in treatment-resistant depression across three clinical trials.'”
Technical details
Endpoint
POSThttps://agentx.sale/x402/classify?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need AI-powered topic classification with confidence scores and human-readable rationale, especially when you want to supply your own label taxonomy or need multi-label support. It is ideal for routing, tagging, and content organization pipelines where explainability matters. Prefer it over keyword extraction when you need discrete category assignments rather than ranked terms.
Side effects
- Text exceeds 24,000 character limit — request rejected
- Empty or missing text field — validation error
- Labels array provided but empty — ambiguous behavior
- Payment not received or USDC balance insufficient — 402 Payment Required
- Malformed JSON body — 400 Bad Request
- Model uncertainty on ambiguous text may produce low-confidence or split labels
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string | |
| labels | array | |
| multiLabel | boolean |
Output
Schema · Response
{
"type": "json",
"example": {
"labels": [
"energy"
],
"confidence": 0.92
}
}Tags
x402
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